Predictive modeling and probabilistic risk assessment of Clostridium perfringens in hamburgers and sandwiches

This study aimed to develop a mathematical model for the survival of Clostridium perfringens in hamburgers and sandwiches and to evaluate their microbial risk. The primary model was developed in hamburgers using 4 strains of C. perfringens at 5, 10, 15, 25 and 37 °C, and the kinetic parameters of the primary model were fitted well with the Weibull model (R ² ≥ 0.95). The secondary model was developed and validated in hamburgers and sandwiches using the Davey model, which was evaluated by B _f , A _f , and RMSE values within the acceptable range. A probabilistic risk model was developed and simulated using @Risk program to estimate the probability of infection (P _inf ) of C. perfringens based on the data on prevalence (n = 100), time, temperature, and consumption of hamburgers and sandwiches (150.00 ± 20.96 g). Based on the simulation model, the mean C. perfringens exposure dose was 0.00976 CFU/g, and the estimated mean P _inf was 1.78 × 10^-13, which was very low in comparison with the current available data. The proposed model and the result can thus be useful to establish risk management options and microbial criteria for C. perfringens contamination in hamburgers and sandwiches.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10068-021-01000-z.

A predictive growth model for Clostridium botulinum during cooling of cooked uncured ground beef

A dynamic model to predict the germination and outgrowth of Clostridium botulinum spores in cooked ground beef was presented. Raw ground beef was inoculated with a ten-strain C. botulinum spore cocktail to achieve approximately 2 log spores/g. The inoculated ground beef was vacuum packaged, cooked to 71 °C to heat shock the spores, cooled to below 10 °C, and incubated isothermally at temperatures from 10 to 46 °C. C. botulinum growth was quantified and fitted into the primary Baranyi Model. Secondary models were fitted to maximum specific growth rate and lag phase duration using Modified Ratkowsky equation (R² 0.96) and hyperbolic function (R² 0.94), respectively. Similar experiments were also performed under non-isothermal (cooling) conditions. Acceptable zone prediction (APZ) analysis was conducted on growth data collected over 3 linear cooling regimes from the current study. The model performance (prediction errors) for all 22 validation data points collected in the current work were within the APZ limits (-1.0 to +0.5 log CFU/g). Additionally, two other growth data sets of C. botulinum reported in the literature were also subjected to the APZ analysis. In these validations, 20/22 and 10/14 predictions fell within the APZ limits. The model presented in this work can be employed to predict C. botulinum spore germination and growth in cooked uncured beef under non-isothermal conditions. The beef industry processors and food service organizations can utilize this predictive microbial model for cooling deviations and temperature abused situations and in developing customized process schedules for cooked, uncured beef products.

Assessing the Performance of Clostridium perfringens Cooling Models for Cooked, Uncured Meat and Poultry Products

Heat-resistant spores of Clostridium perfringens may germinate and multiply in cooked meat and poultry products when the rate and extent of cooling does not occur in a timely manner. Therefore, six cooling models (PMP 7.0 broth model; PMIP uncured beef, chicken, and pork models; Smith-Schaffner version 3; and UK IFR ComBase Perfringens Predictor) were evaluated for relative performance in predicting growth of C. perfringens under dynamic temperature conditions encountered during cooling of cooked, uncured meat and poultry products. The predicted growth responses from the models were extensively compared with those observed in food. Data from 188 time-temperature cooling profiles (176 for single-rate exponential cooling and 12 for dual-rate exponential cooling) were collected from 17 independent sources (16 peer-reviewed publications and one report) for model evaluation. Data were obtained for a variety of cooked products, including meat and poultry slurries, ground meat and poultry products with and without added ingredients (e.g., potato starch, sodium triphosphate, and potassium tetrapyrophosphate), and processed products such as ham and roast beef. Performance of the models was evaluated using three sets of criteria, and accuracy was defined within a 1- to 2-log range. The percentages of accurate, fail-safe, or fail-dangerous predictions for each cooling model differed depending on which criterion was used to evaluate the data set. Nevertheless, the combined percentages of accurate and fail-safe predictions based on the three performance criteria were 34.66 to 42.61% for the PMP 7.0 beef broth model, 100% for the PMIP cooling models for uncured beef, uncured pork and uncured chicken, 80.11 to 93.18% for the Smith-Schaffner cooling model, and 74.43 to 85.23% for the UK IFR ComBase Perfringens Predictor model during single-rate exponential chilling. Except for the PMP 7.0 broth model, the other five cooling models (PMIP, Smith-Schaffner, and UK IFR ComBase) are useful and reliable tools that food processors and regulatory agencies can use to evaluate the safety of cooked or heat-treated uncured meat and poultry products exposed to cooling deviations or to develop customized cooling schedules.

Growth parameters of Escherichia coli O157:H7, Salmonella spp., Listeria monocytogenes, and aerobic mesophilic bacteria of apple cider amended with nisin-EDTA

The effect of nisin (0 or 300 IU/mL), ethylenediamine tetraacetic acid (EDTA, 20 mM), and nisin (300 IU)-EDTA (20 mM) on growth parameters, including lag period (LP) and generation time, of Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella spp. in the presence or absence of aerobic mesophilic bacteria of apple cider during storage at 5 degrees C for up to 16 days or 23 degrees C for 16 h was investigated. The growth data were analyzed and fitted to the modified Gompertz model. The LP values for aerobic mesophilic bacteria of apple cider (control) and those amended with EDTA and nisin during storage at 5 degrees C were 1.61, 1.76, and 5.45 days, respectively. In apple cider stored at 23 degrees C for 16 h, the LP values for the same bacteria and treatment were 3.24, 3.56, and 5.85 h, respectively. The LP values for E. coli O157:H7 determined in the presence of aerobic mesophilic bacteria of apple cider stored at 23 degrees C for 16 h was 1.48 h, while populations for L. monocytogenes and Salmonella in the same cider declined. In sterile apple cider left at 23 degrees C for 16 h, the LP values for E. coli O157:H7, Salmonella, and L. monocytogenes averaged 2.74, 2.37, and 3.16 h, respectively. The generation time for these pathogens were 0.402, 0.260, and 0.187 log (CFU/mL)/h, respectively. Addition of nisin and EDTA combination caused a decline in lag phase duration and the populations for all pathogens tested, suggesting possible addition of this additive to freshly prepared apple cider to enhance its microbial safety and prevent costly recalls.

Risk assessment for Clostridium perfringens in ready-to-eat and partially cooked meat and poultry products

An assessment of the risk of illness associated with Clostridium perfringens in ready-to-eat and partially cooked meat and poultry products was completed to estimate the effect on the annual frequency of illnesses of changing the allowed maximal 1-log growth of C. perfringens during stabilization (cooling after the manufacturing heat step). The exposure assessment modeled stabilization, storage, and consumer preparation such as reheating and hot-holding. The model predicted that assuming a 10- or 100-fold increase from the assumed 1-log (maximal allowable) growth of C. perfringens results in a 1.2- or 1.6-fold increase of C. perfringens-caused illnesses, respectively, at the median of the uncertainty distribution. Improper retail and consumer refrigeration accounted for approximately 90% of the 79,000 C. perfringens illnesses predicted by the model at 1-log growth during stabilization. Improper hot-holding accounted for 8% of predicted illnesses, although model limitations imply that this is an underestimate. Stabilization accounted for less than 1% of illnesses. Efforts to reduce illnesses from C. perfringens in ready-to-eat and partially cooked meat and poultry products should focus on retail and consumer storage and preparation methods.

Influence of four retail food service cooling methods on the behavior of Clostridium perfringens ATCC 10388 in turkey roasts following heating to an internal temperature of 74 degrees C

The influence of four food service cooling methods (CM) on growth of Clostridium perfringens ATCC 10388 in cooked turkey roasts was evaluated. Raw whole turkey roasts were inoculated with C. perfringens spores (approximately 4.23 log CFU per roast), vacuum packaged, and heated to an internal temperature of 74 degrees C. The cooked roasts were cooled as follows: whole roast cut into four quarters and held at 4 degrees C (CM1); whole roast held in a blast chiller (CM2); whole roast loosely wrapped and held at 4 degrees C (CM3); and whole roasts (three per bag) held at 4 degrees C (CM4). The roasts were analyzed for C. perfringens using Shahidi-Ferguson perfringens agar and anaerobic incubation (37 degrees C, 24 h). None of the cooling methods met the amended 2001 U.S. Food and Drug Administration Food Code guidelines for safe cooling of potentially hazardous foods. Times taken for roasts to cool from 57 to 21 degrees C using CM1, CM2, CM3, and CM4 were 2.27, 3.11, 6.22, and 8.71 h, respectively. Times taken for roasts (21 degrees C) to reach 5 degrees C ranged from 6.33 (CM1) to 19.45 h (CM4). Based on initial numbers of C. perfringens, no growth occurred in roasts cooled by CM1 or CM2, whereas numbers increased by 1.5 and 4.0 log in whole roasts cooled via CM3 and CM4, respectively. These findings indicate that certain food service cooling methods for whole cooked turkey roasts may result in proliferation of C. perfringens and increase the risk of foodborne illness by this pathogen.

Predictive model for Clostridium perfringens growth in roast beef during cooling and inhibition of spore germination and outgrowth by organic acid salts

Spores of foodborne pathogens can survive traditional thermal processing schedules used in the manufacturing of processed meat products. Heat-activated spores can germinate and grow to hazardous levels when these products are improperly chilled. Germination and outgrowth of Clostridium perfringens spores in roast beef during chilling was studied following simulated cooling schedules normally used in the processed-meat industry. Inhibitory effects of organic acid salts on germination and outgrowth of C. perfringens spores during chilling and the survival of vegetative cells and spores under abusive refrigerated storage was also evaluated. Beef top rounds were formulated to contain a marinade (finished product concentrations: 1% salt, 0.2% potassium tetrapyrophosphate, and 0.2% starch) and then ground and mixed with antimicrobials (sodium lactate and sodium lactate plus 2.5% sodium diacetate and buffered sodium citrate and buffered sodium citrate plus 1.3% sodium diacetate). The ground product was inoculated with a three-strain cocktail of C. perfringens spores (NCTC 8238, NCTC 8239, and ATCC 10388), mixed, vacuum packaged, heat shocked for 20 min at 75 degrees C, and chilled exponentially from 54.5 to 7.2 degrees C in 9, 12, 15, 18, or 21 h. C. perfringens populations (total and spore) were enumerated after heat shock, during chilling, and during storage for up to 60 days at 10 degrees C using tryptose-sulfite-cycloserine agar. C. perfringens spores were able to germinate and grow in roast beef (control, without any antimicrobials) from an initial population of ca. 3.1 log CFU/g by 2.00, 3.44, 4.04, 4.86, and 5.72 log CFU/g after 9, 12, 15, 18, and 21 h of exponential chilling. A predictive model was developed to describe sigmoidal C. perfringens growth curves during cooling of roast beef from 54.5 to 7.2 degrees C within 9, 12, 15, 18, and 21 h. Addition of antimicrobials prevented germination and outgrowth of C. perfringens regardless of the chill times. C. perfringens spores could be recovered from samples containing organic acid salts that were stored up to 60 days at 10 degrees C. Extension of chilling time to > or =9 h resulted in >1 log CFU/g growth of C. perfringens under anaerobic conditions in roast beef. Organic acid salts inhibited outgrowth of C. perfringens spores during chilling of roast beef when extended chill rates were followed. Although C. perfringens spore germination is inhibited by the antimicrobials, this inhibition may represent a hazard when such products are incorporated into new products, such as soups and chili, that do not contain these antimicrobials, thus allowing spore germination and outgrowth under conditions of temperature abuse.

Development of an integrated model for heat transfer and dynamic growth of Clostridium perfringens during the cooling of cooked boneless ham

Numerous small meat processors in the United States have difficulties complying with the stabilization performance standards for preventing growth of Clostridium perfringens by 1 log10 cycle during cooling of ready-to-eat (RTE) products. These standards were established by the Food Safety and Inspection Service (FSIS) of the US Department of Agriculture in 1999. In recent years, several attempts have been made to develop predictive models for growth of C. perfringens within the range of cooling temperatures included in the FSIS standards. Those studies mainly focused on microbiological aspects, using hypothesized cooling rates. Conversely, studies dealing with heat transfer models to predict cooling rates in meat products do not address microbial growth. Integration of heat transfer relationships with C. perfringens growth relationships during cooling of meat products has been very limited. Therefore, a computer simulation scheme was developed to analyze heat transfer phenomena and temperature-dependent C. perfringens growth during cooling of cooked boneless cured ham. The temperature history of ham was predicted using a finite element heat diffusion model. Validation of heat transfer predictions used experimental data collected in commercial meat-processing facilities. For C. perfringens growth, a dynamic model was developed using Baranyi's nonautonomous differential equation. The bacterium's growth model was integrated into the computer program using predicted temperature histories as input values. For cooling cooked hams from 66.6 degrees C to 4.4 degrees C using forced air, the maximum deviation between predicted and experimental core temperature data was 2.54 degrees C. Predicted C. perfringens growth curves obtained from dynamic modeling showed good agreement with validated results for three different cooling scenarios. Mean absolute values of relative errors were below 6%, and deviations between predicted and experimental cell counts were within 0.37 log10 CFU/g. For a cooling process which was in exact compliance with the FSIS stabilization performance standards, a mean net growth of 1.37 log10 CFU/g was predicted. This study introduced the combination of engineering modeling and microbiological modeling as a useful quantitative tool for general food safety applications, such as risk assessment and hazard analysis and critical control points (HACCP) plans.

Development of a model to predict growth of Clostridium perfringens in cooked beef during cooling

The objective of this work was to develop a new model to predict the growth of Clostridium perfringens in cooked meat during cooling. All data were collected under changing temperature conditions. Individual growth curves were fit using DMFit. Germination outgrowth and lag (GOL) time was modeled versus temperature at the end of GOL using conservative assumptions. Each growth curve was used to estimate a series of exponential growth rates at a series of temperatures. The squareroot model was used to describe the relationship between the square root of the average exponential growth rate and effective temperature. Predictions from the new model were in close agreement with the data used to create the model. When predictions from the model were compared with new observations, fail-dangerous predictions were made a majority of the time. When GOL time was predicted exactly, many fail-dangerous predictions shifted toward the fail-safe direction. Two important facts regarding C. perfringens should impact future modeling research with this organism and may have broader food safety policy implications: (i) the normal variability in the response of the organism from replicate to replicate may be quite large (1 log CFU) and may exceed the current U.S. Food Safety Inspection Service performance standard, and (ii) the accuracy of the GOL time model has a profound influence upon the overall prediction, with small differences in GOL time prediction (approximately 1 h) having a very large effect on the predicted final concentration of C. perfringens.

Modeling growth of Clostridium perfringens in pea soup during cooling

Clostridium perfringens is a pathogen that mainly causes food poisoning outbreaks when large quantities of food are prepared. Therefore, a model was developed to predict the effect of different cooling procedures on the growth of this pathogen during cooling of food: Dutch pea soup. First, a growth rate model based on interpretable parameters was used to predict growth during linear cooling of pea soup. Second, a temperature model for cooling pea soup was constructed by fitting the model to experimental data published earlier. This cooling model was used to estimate the effect of various cooling environments on average cooling times, taking into account the effect of stirring and product volume. The growth model systematically overestimated growth of C. perfringens during cooling in air, but this effect was limited to less than 0.5 log N/ml and this was considered to be acceptable for practical purposes. It was demonstrated that the growth model for C. perfringens combined with the cooling model for pea soup could be used to sufficiently predict growth of C. perfringens in different volume sizes of pea soup during cooling in air as well as the effect of stirring, different cooling temperatures, and various cooling environments on the growth of C. perfringens in pea soup. Although fine-tuning may be needed to eliminate inaccuracies, it was concluded that the combined model could be a useful tool for designing good manufacturing practices (GMP) procedures.

Behavior of Clostridium perfringens at low temperatures

Refrigerated storage is an important step in the preparation of foods and inadequate storage is one of the main causes of food poisoning outbreaks of Clostridium perfringens. Therefore, growth and germination characteristics of C. perfringens in a temperature range of 3-42 degrees C were determined in fluid thioglycollate broth (FTG) and Dutch pea soup. To study the effect of adaptation, cells were either inoculated from a 37 degrees C pre-culture or from a temperature-adapted pre-culture. Membrane fatty acid patterns were determined at all temperatures to examine the effect of temperature on membrane composition. Spores were either inoculated with and without heat treatment. Adaptation of cells did not influence growth rate nor lag phase. Growth in pea soup, however, was slower and lag phases tended to be more extended compared to FTG. No growth was observed at temperatures < or =10 degrees C and death rates in pea soup were higher than those in FTG at these low temperatures. Cells preserved the membrane fluidity by reducing the arachidic acid content and increasing the lauric acid content when the temperature dropped. This resulted in a net reduction in chain length. Microscopic analysis of cells grown at 15 degrees C revealed a morphological change: cells were elongated compared to those grown at 37 degrees C. These data demonstrate the ability of C. perfringens to adapt to lower temperatures. However, this did not influence growth characteristics compared to non-adapted cells. Spores of C. perfringens did germinate at all temperatures with and without heat-activation. Combining this fact with the extended survival at low temperatures emphasizes the need for adequate heating of refrigerated foods before consumption to eliminate health risks due to C. perfringens.

Growth potential of Clostridium perfringens during cooling of cooked meats

Many meat-based food products are cooked to temperatures sufficient to inactivate vegetative cells of Clostridium perfringens, but spores of this bacterium can survive, germinate, and grow in these products if sufficient time, temperature, and other variables exist. Because ingestion of large numbers of vegetative cells can lead to concomitant sporulation, enterotoxin release in the gastrointestinal tract, and diarrhea-like illness, a necessary food safety objective is to ensure that not more than acceptable levels of C. perfringens are in finished products. As cooked meat items cool they will pass through the growth temperature range of C. perfringens (50 to 15 degrees C). Therefore, an important step in determining the likely level of C. perfringens in the final product is the estimation of growth of the pathogen during cooling of the cooked product. Numerous studies exist dealing with just such estimations, yet consensual methodologies, results, and conclusions are lacking. There is a need to consider the bulk of C. perfringens work relating to cooling of cooked meat-based products and attempt to move toward a better understanding of the true growth potential of the organism. This review attempts to summarize observations made by researchers and highlight variations in experimental approach as possible explanations for different outcomes. An attempt is also made here to identify and justify optimal procedures for conducting C. perfringens growth estimation in meat-based cooked food products during cooling.

Evaluation of a predictive model for Clostridium perfringens growth during cooling

Proper temperature control is essential in minimizing Clostridium perfringens germination, growth, and toxin production. The U.S. Department of Agriculture Food Safety and Inspection Service offers two options for the cooling of meat products: follow a standard time-temperature schedule or validate that alternative cooling regimes result in no more than a 1-log CFU/g increase of C. perfringens and no growth of Clostridium botulinum. The Juneja 1999 model for C. perfringens growth during cooling may be helpful in determining whether the C. perfringens performance standard has been achieved, but this model has not been extensively validated. The objective of this study was to validate the Juneja 1999 model under a variety of temperature situations. The Juneja 1999 model for C. perfringens growth during cooling is fail safe when low (<1 log CFU/ml) or high (>3 log CFU/ml) observed increases occur during exponential cooling. The Juneja 1999 model consistently underpredicted growth at intermediate observed increases (1 to 3 log CFU/ml). The Juneja 1999 model also underpredicted growth whenever exponential cooling took place at two different rates in the first and second portions of the cooling process. This error may be due to faster than predicted growth of C. perfringens cells during cooling or to an inaccuracy in the Juneja 1999 model.

Evaluation of a Clostridium perfringens predictive model, developed under isothermal conditions in broth, to predict growth in ground beef during cooling

Proper temperature control is essential in minimizing Clostridium perfringens germination, growth, and toxin production. The U.S. Department of Agriculture (USDA) Food Safety and Inspection Service (FSIS) offers two options for the cooling of meat products: follow a standard time-temperature schedule or validate that alternative cooling regimens result in no more than a 1-log(10) CFU/g increase of C. perfringens and no growth of Clostridium botulinum. A mathematical model developed by Juneja et al. (Food Microbiol. 16:335-349, 1999) may be helpful in determining if the C. perfringens performance standard has been achieved, but this model has not been extensively validated. The objective of this study was to validate the Juneja 1999 model in ground beef under a variety of changing temperature and temperature abuse situations. The Juneja 1999 model consistently underpredicted growth of C. perfringens during exponential cooling of ground beef. The model also underpredicted growth of C. perfringens in ground beef cooled at two different rates. The results presented here show generally good agreement with published data on the growth of C. perfringens in similar products. The model error may be due to faster-than-expected exponential growth rates in ground beef during cooling or an error in the mathematical formulation of the model.

Dynamic computer simulation of Clostridium perfringens growth in cooked ground beef

The objective of this study was to develop a computer simulation algorithm to dynamically estimate and predict the growth of Clostridium perfringens in cooked ground beef. The computational algorithm was based on the implicit form of the Gompertz model, the growth kinetics of C. perfringens in cooked ground beef, and the fourth-order Runge-Kutta numerical method. This algorithm was validated using a cocktail of three strains of C. perfringens spores grown under isothermal, square-waved, linear cooling, and exponential cooling temperature profiles. In general, the results of computer simulation matched closely with the experimental data with the absolute errors less than 0.5 log(10) CFU/g. This method may be a useful tool for the food industry, regulatory agencies, distributors, and retailers to predict the effect of temperature abuse on the microbial safety of C. perfringens and other foodborne pathogens in processed meat products.

Cooling rate effect on outgrowth of Clostridium perfringens in cooked, ready-to-eat turkey breast roasts

The potential for Clostridium perfringens spores to germinate and grow in cooked, ready-to-eat turkey products was evaluated to determine a safe cooling rate within the critical temperatures of 48.9 C (120 F) through 12.8 C (55 F). Raw turkey deli breast roasts were inoculated with a cocktail of C. perfringens spores (NCTC 8238, NCTC 8239, and NCTC 10388) and cooked in a steam oven to an internal temperature of 72 C. The sample roasts were then cooled through the critical cooling range at rates yielding cooling times of 6, 8, and 10 h. Turkey roasts were analyzed for spore growth and multiplication using tryptose-sulfite-cycloserine agar and anaerobic incubation at 37 C for 48 h. Cooling times of 6 and 8 h showed no proliferation of C. perfringens that would violate the USDA/Food Safety Inspection Service safe cooling standard criteria, which would allow no more than a 1 log10 multiplication between 48.9 and 12.8 C. A 9.6-h cooling period between the designated temperatures at a 95% confidence interval was determined to be adequate for nonproliferation of C. perfringens. On the other hand, a 95% tolerance interval would be more stringent in that it suggests no more than an 8.9-h cooling period. Tolerance intervals required that 95% of all our observations did not exceed the limit of 1 log10 increase in C. perfringens. This study indicated that in cooked, ready-to-eat turkey deli breasts, a cooling period between 48.9 C (120 F) and 12.8 C (55 F) of no greater than 8.9 h should be utilized to prevent possible C. perfringens foodborne outbreaks.